A Computational Model of Gene Regulatory Networks and its Topological Properties

A new model for Gene Regulatory Networks (GRN) is proposed. The model is potentially more biologically sound than other approaches, and is based on the idea of an artificial genome from which several products like genes, mRNA, miRNA, non-coding RNA, and proteins are extracted. These products are connected giving rise to a heterogeneous directed graph. The topology of the obtained networks is studied using degree distributions. We make some considerations about the biological meaning of the outcomes of these simulations.

[1]  R. Shiekhattar,et al.  MicroRNA biogenesis: isolation and characterization of the microprocessor complex. , 2006, Methods in molecular biology.

[2]  W. Banzhaf Artificial Regulatory Networks and Genetic Programming , 2003 .

[3]  M. Newman,et al.  Random graphs with arbitrary degree distributions and their applications. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Hitoshi Iba,et al.  Inference of gene regulatory networks using s-system and differential evolution , 2005, GECCO '05.

[5]  M. M. Novak Complexus mundi: emergent patterns in nature , 2006 .

[6]  Torsten Reil,et al.  Dynamics of Gene Expression in an Artificial Genome - Implications for Biological and Artificial Ontogeny , 1999, ECAL.

[7]  A. Sali,et al.  Protein Structure Prediction and Structural Genomics , 2001, Science.

[8]  Nicholas Geard,et al.  Modelling gene regulatory networks: systems biology to complex systems , 2004 .

[9]  H E Stanley,et al.  Classes of small-world networks. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[10]  M. Rosbash,et al.  Identification of eight proteins that cross-link to pre-mRNA in the yeast commitment complex. , 1999, Genes & development.

[11]  Hitoshi Iba,et al.  Inference of gene regulatory model by genetic algorithms , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[12]  Janet Wiles,et al.  Evolving Genetic Regulatory Networks Using an Artificial Genome , 2004, APBC.

[13]  Janet Wiles,et al.  Dynamics of gene expression in an artificial genome , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[14]  Fred Winston,et al.  Intergenic transcription is required to repress the Saccharomyces cerevisiae SER3 gene , 2004, Nature.

[15]  Stephanie Forrest,et al.  Reconstructing gene networks from large scale gene expression data , 2000 .

[16]  Andrew D. Ellington,et al.  AANT: the Amino Aciduchleotide Interaction Database , 2004, Nucleic Acids Res..

[17]  Janet Wiles,et al.  Towards more biological mutation operators in gene regulation studies. , 2004, Bio Systems.

[18]  H. Iba,et al.  Inferring a system of differential equations for a gene regulatory network by using genetic programming , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[19]  Stuart A. Kauffman,et al.  The origins of order , 1993 .